Spatio-temporal analysis of brain MRI images using hidden Markov models

Ying Wang*, Susan M. Resnick, Christos Davatzikos

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

7 Citations (Scopus)

Abstract

A rapidly increasing number of medical imaging studies is longitudinal, i.e. involves series of repeated examinations of the same individuals. This paper presents a methodology for analysis of such 4D images, with brain aging as the primary application. An adaptive regional clustering method is first adopted to construct a spatial pattern, in which a measure of correlation between morphological measurements and a continuous patient's variable (age in our case) is used to group brain voxels into regions; Secondly, a dynamic probabilistic Hidden Markov Model (HMM) is created to statistically analyze the relationship between spatial brain patterns and hidden states; Thirdly, parametric HMM models under a bagging framework are used to capture the changes occurring with time by decoding the hidden states longitudinally. We apply this method to datasets from elderly individuals, and test the effectiveness of this spatio-temporal model in analyzing the temporal dynamics of spatial aging patterns on an individual basis. Experimental results show this method could facilitate the early detection of pathological brain change.

Original languageEnglish
Title of host publicationMedical Image Computing and Computer-Assisted Intervention, MICCAI2010 - 13th International Conference, Proceedings
Place of PublicationBeijing, China
PublisherSpringer, Springer Nature
Pages160-168
Number of pages9
Volume6362 LNCS
EditionPART 2
ISBN (Electronic)9783642157455
ISBN (Print)9783642157448
DOIs
Publication statusPublished - 2010
Externally publishedYes
Event13th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2010 - Beijing, China
Duration: 20 Sep 201024 Sep 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume6362 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other13th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2010
CountryChina
CityBeijing
Period20/09/1024/09/10

    Fingerprint

Cite this

Wang, Y., Resnick, S. M., & Davatzikos, C. (2010). Spatio-temporal analysis of brain MRI images using hidden Markov models. In Medical Image Computing and Computer-Assisted Intervention, MICCAI2010 - 13th International Conference, Proceedings (PART 2 ed., Vol. 6362 LNCS, pp. 160-168). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6362 LNCS, No. PART 2). Beijing, China: Springer, Springer Nature. https://doi.org/10.1007/978-3-642-15745-5_20